Department of Biological Sciences, Purdue University, 915 West State Street, West Lafayette, IN 47907, USA.
J Cheminform. 2009 Dec 17;1:19. doi: 10.1186/1758-2946-1-19.
The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed.
In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability.
The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.
从化合物的大型数据库中鉴定有前途的药物先导物是药物设计初步阶段的重要步骤。尽管形状已知在分子识别过程中起着关键作用，但在编码方案和速度方面，其在虚拟筛选中的应用都存在重大障碍。
在这项研究中，我们研究了对齐无关的三维 Zernike 描述符（3DZD）在快速基于形状的相似性搜索中的功效。该方法的性能与其他几种方法（包括基于统计矩的超快形状识别方案（USR）和 SIMCOMP，一种比较原子环境的图匹配算法）进行了比较。使用三个基准数据集根据其分子分类能力、检索率以及在模拟实际虚拟筛选任务情况下在大型药物数据库上的性能，对这些方法进行了彻底的测试。3DZD 的表现优于或与其他方法相当，具体取决于使用的数据集和评估指标。调查了基于形状的方法在特定情况下成功和失败的原因。根据三个数据集的结果，得出了关于它们的效率和适用性的一般结论。
3DZD 具有快速比较化合物三维形状的独特能力。分析的示例说明了 3DZD 的优势和改进空间。
